3F0Q

Staphylococcus aureus dihydrofolate reductase complexed with NADPH and 2,4-Diamino-5-[3-(3-methoxy-5-(2,6-dimethylphenyl)phenyl)but-1-ynyl]-6-methylpyrimidine

Summary for 3F0Q

• Entry DOI: 10.2210/pdb3f0q/pdb
• Related: 3F0B 3F0S 3F0U 3F0V 3F0X
• Descriptor: Trimethoprim-sensitive dihydrofolate reductase, NADPH DIHYDRO-NICOTINAMIDE-ADENINE-DINUCLEOTIDE PHOSPHATE, 5-[(3S)-3-(5-methoxy-2',6'-dimethylbiphenyl-3-yl)but-1-yn-1-yl]-6-methylpyrimidine-2,4-diamine, ... (4 entities in total)
• Functional Keywords: oxidoreductase
• Biological source: Staphylococcus aureus RF122
• Total number of polymer chains: 1
• Total formula weight: 19147.47

Authors

Anderson, A.C.,Frey, K.M.,Liu, J.,Lombardo, M.N. (deposition date: 2008-10-25, release date: 2009-10-06, Last modification date: 2024-04-03)

Primary citation

Frey, K.M.,Georgiev, I.,Donald, B.R.,Anderson, A.C.
Predicting resistance mutations using protein design algorithms.
Proc.Natl.Acad.Sci.USA, 107:13707-13712, 2010

PubMed Abstract: Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.

PubMed: 20643959
DOI: 10.1073/pnas.1002162107

Experimental method

X-RAY DIFFRACTION (2.08 Å)